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Best α-helical transmembrane protein topology predictions are achieved using hidden Markov models and evolutionary information

Methods that predict the topology of helical membrane proteins are standard tools when analyzing any proteome. Therefore, it is important to improve the performance of such methods. Here we introduce a novel method, PRODIV-TMHMM, which is a profile-based hidden Markov model (HMM) that also incorpora...

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書誌詳細
主要な著者: Viklund, Håkan, Elofsson, Arne
フォーマット: Artigo
言語:Inglês
出版事項: Cold Spring Harbor Laboratory Press 2004
主題:
オンライン・アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC2279939/
https://ncbi.nlm.nih.gov/pubmed/15215532
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1110/ps.04625404
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